edgegate_llm_compile

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description fully discloses key behavioral traits: async pattern (returns job ID for polling), cost gating with a specific cap default, artifact composition (composite QNN_DLC + 3 components), and the truth that target_runtime is QNN_DLC despite the genie label. This goes far beyond schema fields, providing actionable expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Four sentences, no filler. The action is front-loaded, and every subsequent sentence adds unique value (return value, polling, cost cap, artifact structure, runtime nuance).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the medium complexity and absence of annotations/output schema, the description covers the core lifecycle: submit, get job ID, poll with the sibling tool, plus cost and output details. Missing are failure scenarios and explicit parameter requirements, but the essentials are present.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has zero parameter descriptions, so the description must compensate. It adds meaning for target_runtime (QNN_DLC under the hood) and alludes to source_artifact_ids via 'multi-component' and '3 component artifacts', but leaves roles, context_lengths, and sequence_lengths unexplained. Partial compensation only.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States the exact action: submits a multi-component LLM compile + link job via Qualcomm AI Hub. The description distinguishes it from the sibling status checker by noting the returned compile_job_id and polling tool. It also preemptively clarifies the genie label nuance, further setting it apart from edgegate_compile_genie.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Instructs the user to poll with edgegate_check_llm_compile_status, which defines the follow-up action. It sets expectations for the compile process and cost gating, giving context on when this tool is appropriate. It does not explicitly list when-not-to-use scenarios or alternatives beyond the status poll.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.